Remote Machine Condition Monitoring for the Remote Employee

Industry continues to face the challenge of adapting their people and procedures to meet the need for remote work and overcoming the practicalities of having a greater physical distance between humans and machines. Although technology continues to advance, making the equipment and tools we use more efficient, they still require machine condition monitoring to ensure they’re operating correctly. However, when it’s impractical — or impossible — for humans to perform this vital task, the solution is moving monitoring machine condition to the edge.

What is Machine Condition Monitoring?

Machine condition monitoring, in general, provides visibility into a machine’s status or “health.” Depending on what the machine does, equipment manufacturers and operators pinpoint parameters that allow them to gauge a machine’s health, such as:

  • Temperature
  • Energy use
  • Vibration
  • RPM/speed
  • Output

Operators are happy to see a good machine health score, but the primary benefit of machine condition monitoring is revealing when something is wrong. When monitoring reveals that performance or parameters fall outside from normal ranges, operators can inspect the equipment, troubleshoot, and make adjustments or repair — rather than dealing with catastrophic failure later.

The investment that businesses and enterprises make in machine condition monitoring can have a huge return by preventing downtime. Unplanned downtime results in lost revenues from an inability to make products or provide services. However, the costs of downtime also add up in additional ways. Losses include paying for nonproductive labor, fines for noncompliance, and, possibly, lost customers. Equipment failure itself can lead to product defects, and waste.

Moreover, the costs of repairing equipment after a catastrophic failure are much higher, and it takes much longer than addressing minor issues as they arise. Analysis of downtime’s impact reveals that these costs can be overwhelming. The automotive industry, for example, estimates that downtime costs from $22,000 to $50,000per minute.  

You can also add soft costs to downtime’s impact. If it’s a recurring problem for a business or enterprise, it can negatively affect employee morale, work culture, and the ability to innovate.

When people and machines are all under one roof, it’s possible for operators to visually inspect and personally monitor equipment. Manual monitoring and health check analysis, however, can be a time-consuming and inefficient use of resources. Some plants shut down completely each month to perform maintenance and health check procedures.

Manual processes can also be ineffective — staff may log parameters in a spreadsheet, identifying any points of failure, but never use that data to understand the warning signs that future issues are likely.  In other cases, manufacturing engineers know their machines inside and out, but that knowledge isn’t documented or easily shared throughout the company. Those businesses may be relying too heavily on just a few people to recognize the signs that equipment is heading for failure.

In a crisis situation, when a plant is operating with fewer resources, one of the first things operators do is suspend predictive maintenance and planned downtime. Unfortunately, this strategy, meant to help increase output — or even change production, for example, from beverages to hand sanitizer — can backfire. Without machine condition monitoring, operators lose visibility and can make poor decisions, running machines that will fail without maintenance — and cause the downtime the enterprise cannot afford.

Machine Condition Monitoring at the Edge

A better option than manual processes is machine condition monitoring at the edge. These systems use sensors, edge gateways, and edge IoT software to automate data collection and analysis. When an edge solution detects a reading outside of preset limits, it can alert operators that the equipment needs their immediate attention.

Unlike manual processes, machine monitoring at the edge is automatic and continuous — and it doesn’t require specific personnel to be nearby. Additionally, it gives operators a complete picture of the machine’s health rather than just data on one parameter such as vibration or
RPM or data at a single point in time. It shows you how the machine has operated historically and enables more accurate predictions of how it will behave next.

Ultimately, it helps manufacturers maximize machine uptime. The data from remote monitoring can eliminate the need for a complete or routine shutdowns for inspections. Instead, operators can use a plan of targeted shutdowns, only when health checks indicate the need.

Additionally, machine condition monitoring at the edge is more practical for mission-critical operations or highly sensitive machinery. Data is processed close to the source, eliminating latency that can occur when it’s transmitted to and from the cloud. Handling monitoring at the edge enables real-time response to changes and immediate action that can save thousands of dollars in equipment repair or downtime costs.

The Journey to Optimized Machine Condition Monitoring

Operations transitioning to predictive failure analysis via edge systems often progress through three steps: 

  1. Remote monitoring: This first step often delivers substantial value to an organization by providing greater visibility into operations and the ability to manage and, in some cases, maintain equipment remotely.
  2. Health scoring: Machine condition monitoring at the edge requires setting limits on parameters that show whether or not the equipment is functioning normally. 
  3. Predict failure potential and need for intervention: When monitored metrics fall outside of acceptable thresholds, the system can take action — from alerting engineers or stopping a production line to enabling remote maintenance to correct the problem.

Remote machine condition monitoring can also be valuable when deploying new equipment, enabling remote configuration and remote access. When remote work scaled in 2020, for example, machine condition monitoring at the edge enabled companies to protect their investment in mobile equipment by ensuring it was properly configured and used according to corporate policies.

Support for a Safer, More Productive Work Environment 

Machine condition monitoring at the edge has also proven its value through automation and remote access in operations that have reinvented processes to conform to social distancing policies. Machine condition monitoring at the edge enables engineers and operators to access the data they need from a distance, rather than relying on in-person monitoring and service that could put employees’ health at risk and increase the company’s liability. With some workforces reduced by up to 40 percent, the ability to collect machine health data, analyze it, and share it with all personnel is crucial when staff that is typically responsible isn’t available.

Although the benefits of evolving from manual processes to machine condition monitoring at the edge are indisputable, it may take your team some time to adopt an automated edge system. Plant managers and engineers may prefer to maintain control — and possibly be concerned that tech will make their jobs less secure. It’s wise to take steps to evolve your company culture as you take the journey from manual monitoring processes to remote monitoring and automation.

Remind your team that machine condition monitoring at the edge not only has benefits for your business as a whole but also for their individual roles. Without the burden of manually inspecting equipment, engineers and operators will have more time to devote to other parts of their jobs, including maximizing output, reducing cost, improving efficiency, and innovation — while machine condition monitoring at the edge has equipment health covered.

To learn more about ADLINK’s machine health solutions for remote monitoring visit us here.

Author: Daniel Collins
Author: Daniel Collins

Senior Director of Edge Solutions at ADLINK Technology USA